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1.  Mild hypoglycemia is strongly associated with increased intensive care unit length of stay 
Background
Hypoglycemia is associated with increased mortality in critically ill patients. The impact of hypoglycemia on resource utilization has not been investigated. The objective of this investigation was to evaluate the association of hypoglycemia, defined as a blood glucose concentration (BG) < 70 mg/dL, and intensive care unit (ICU) length of stay (LOS) in three different cohorts of critically ill patients.
Methods
This is a retrospective investigation of prospectively collected data, including patients from two large observational cohorts: 3,263 patients admitted to Stamford Hospital (ST) and 2,063 patients admitted to three institutions in The Netherlands (NL) as well as 914 patients from the GLUCONTROL trial (GL), a multicenter prospective randomized controlled trial of intensive insulin therapy.
Results
Patients with hypoglycemia were more likely to be diabetic, had higher APACHE II scores, and higher mortality than did patients without hypoglycemia. Patients with hypoglycemia had longer ICU LOS (median [interquartile range]) in ST (3.0 [1.4-7.1] vs. 1.2 [0.8-2.3] days, P < 0.0001), NL (5.2 [2.6-10.3] vs. 2.0 [1.3-3.2] days, P < 0.0001), and GL (9 [5-17] vs. 5 [3-9] days, P < 0.0001). For the entire cohort of 6,240 patients ICU LOS was 1.8 (1.0-3.3) days for those without hypoglycemia and 3.0 (1.5-6.7) days for those with a single episode of hypoglycemia (P < 0.0001). This was a consistent finding even when patients were stratified by severity of illness or survivor status. There was a strong positive correlation between the number of episodes of hypoglycemia and ICU LOS among all three cohorts.
Conclusions
This multicenter international investigation demonstrated that hypoglycemia was consistently associated with significantly higher ICU LOS in heterogeneous cohorts of critically ill patients, independently of severity of illness and survivor status. More effective methods to prevent hypoglycemia in these patients may positively impact their cost of care.
doi:10.1186/2110-5820-1-49
PMCID: PMC3273438  PMID: 22115519
hypoglycemia; intensive care unit; length of stay; resource utilization; APACHE II; mortality; intensive insulin therapy
2.  Statins in the critically ill 
The use or misuse of statins in critically ill patients recently attracted the attention of intensive care clinicians. Indeed, statins are probably the most common chronic treatment before critical illness and some recent experimental and clinical data demonstrated their beneficial effects during sepsis, acute lung injury (ALI)/acute respiratory distress syndrome (ARDS), or after aneurismal subarachnoidal hemorrhage (aSAH). Due to the heterogeneity of current studies and the lack of well-designed prospective studies, definitive conclusions for systematic and large-scale utilization in intensive care units cannot be drawn from the published evidence. Furthermore, the extent of statins side effects in critically ill patients is still unknown. For the intensive care clinician, it is a matter of individually identifying the patient who can benefit from this therapy according to the current literature. The purpose of this review is to describe the mechanisms of actions of statins and to synthesize the clinical data that underline the relevant effects of statins in the particular setting of critical care, in an attempt to guide the clinician through his daily practice.
doi:10.1186/2110-5820-2-19
PMCID: PMC3488539  PMID: 22709377
Mevalonate; HMG-CoA reductase; Sepsis; Acute lung injury; Acute respiratory distress syndrome; Subarachnoid hemorrhage
3.  Accuracy and limitations of continuous glucose monitoring using spectroscopy in critically ill patients 
Background
OptiScanner devices, continuous glucose monitoring devices that perform automated blood draws via a central venous catheter and create plasma through centrifugation, measure plasma glucose levels through mid-infrared spectroscopy at the bedside. The objective of this study was to determine accuracy and practicality of the devices in critically ill patients attempting glycemic control.
Methods
The plasma glucose level was measured by the devices and in comparative plasma samples using Yellow Springs Instrument (YSI) plasma analyzers. After adding several previously unrecognized interferences in the interference library, we reanalyzed the mid-infrared signals and compared the resulting plasma glucose level with the reference value. Results are presented in Clarke error grids, glucose prediction errors and Bland-Altman plots and expressed as correlation coefficients.
Results
We analyzed 463 comparative samples from 71 patients (median 6 (4 to 9) samples per patient). After calibrating the system, a Clarke error grid showed 100% of the values in zones A or B. The glucose predictor error demonstrated that 86% of the glucose values < 75 mg/dL were within ± 15 mg/dL of the YSI results and 95% ≥ 75 mg/dL were within 20% of the comparative YSI results. Bland-Altman plot showed a bias of −0.6 with limit of agreement of −24.6 to 23.3. The Pearson correlation coefficient was 0.93 and R2 was 0.87. In one third of the patients the devices had to be disconnected prematurely (that is before planned disconnection) because of repeated occlusion alarms suggesting blood draw errors.
Conclusion
The devices needed calibration for several previously unrecognized interferences. Thereafter, accuracy of the device to measure plasma glucose levels in ‘our cohort’ of critically ill patients improved, but external validation is highly recommended. The automated blood draw system of the devices needs further improvement to make this device of value for clinical use (trial registration (Netherlands Trial Register): NTR2864).
doi:10.1186/2110-5820-4-8
PMCID: PMC3975731  PMID: 24598381
Glucose; Spectroscopy; Point-of-care; Monitoring; ICU
4.  Variability of insulin sensitivity during the first 4 days of critical illness: implications for tight glycemic control 
Background
Effective tight glycemic control (TGC) can improve outcomes in critical care patients, but it is difficult to achieve consistently. Insulin sensitivity defines the metabolic balance between insulin concentration and insulin-mediated glucose disposal. Hence, variability of insulin sensitivity can cause variable glycemia. This study quantifies and compares the daily evolution of insulin sensitivity level and variability for critical care patients receiving TGC.
Methods
This is a retrospective analysis of data from the SPRINT TGC study involving patients admitted to a mixed medical-surgical ICU between August 2005 and May 2007. Only patients who commenced TGC within 12 hours of ICU admission and spent at least 24 hours on the SPRINT protocol were included (N = 164). Model-based insulin sensitivity (SI) was identified each hour. Absolute level and hour-to-hour percent changes in SI were assessed on cohort and per-patient bases. Levels and variability of SI were compared over time on 24-hour and 6-hour timescales for the first 4 days of ICU stay.
Results
Cohort and per-patient median SI levels increased by 34% and 33% (p < 0.001) between days 1 and 2 of ICU stay. Concomitantly, cohort and per-patient SI variability decreased by 32% and 36% (p < 0.001). For 72% of the cohort, median SI on day 2 was higher than on day 1. The day 1–2 results are the only clear, statistically significant trends across both analyses. Analysis of the first 24 hours using 6-hour blocks of SI data showed that most of the improvement in insulin sensitivity level and variability seen between days 1 and 2 occurred during the first 12–18 hours of day 1.
Conclusions
Critically ill patients have significantly lower and more variable insulin sensitivity on day 1 than later in their ICU stay and particularly during the first 12 hours. This rapid improvement is likely due to the decline of counter-regulatory hormones as the acute phase of critical illness progresses. Clinically, these results suggest that while using TGC protocols with patients during their first few days of ICU stay, extra care should be afforded. Increased measurement frequency, higher target glycemic bands, conservative insulin dosing, and modulation of carbohydrate nutrition should be considered to minimize safely the outcome glycemic variability and reduce the risk of hypoglycemia.
doi:10.1186/2110-5820-2-17
PMCID: PMC3464183  PMID: 22703645
Critical care; Hyperglycemia; Insulin resistance; Mathematical model; Algorithms

Results 1-4 (4)